thepian commited on
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Fine-tuned on eco-products domain (brand, product name, origin)

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-4.0
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+ base_model: bltlab/queryner-bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: checkpoints
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # checkpoints
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+
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+ This model is a fine-tuned version of [bltlab/queryner-bert-base-uncased](https://huggingface.co/bltlab/queryner-bert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1054
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.9302 | 1.0 | 797 | 0.1401 |
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+ | 0.163 | 2.0 | 1594 | 0.1058 |
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+ | 0.1035 | 3.0 | 2391 | 0.1054 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.6
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+ - Pytorch 2.9.0
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+ - Datasets 3.2.0
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+ - Tokenizers 0.22.2
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "B-UoM",
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+ "1": "B-color",
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+ "2": "B-condition",
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+ "3": "B-content",
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+ "4": "B-core_product_type",
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+ "5": "B-creator",
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+ "6": "B-department",
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+ "7": "B-material",
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+ "8": "B-modifier",
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+ "9": "B-occasion",
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+ "10": "B-origin",
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+ "11": "B-price",
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+ "12": "B-product_name",
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+ "13": "B-product_number",
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+ "14": "B-quantity",
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+ "15": "B-shape",
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+ "16": "B-time",
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